Bear Grass, NC
How exposed is Bear Grass to wildfire?
Bear Grass's 98 buildings earn a 46th-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Bear Grass at the 46th percentile, close to its 46th-percentile risk score.
What "at risk" means for the buildings here
57.1% of Bear Grass's 98 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 42.9% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Bear Grass against the rest of the country
Bear Grass ranks lower within North Carolina (30th percentile statewide) than its 46th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Bear Grass ranks 16,935 for wildfire risk (1 is highest) and 29,141 by building count (1 is largest). Within North Carolina alone, it ranks 542 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
What this risk score means for insurance
Bear Grass's elevated rating (46th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
Bear Grass's 57.1% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Bear Grass's figures come from
Every one of the two percentiles behind Bear Grass's 16,935-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Bear Grass's dominant indirect exposure actually means, with real examples from across the dataset.